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. The position gives excellent opportunities in publishing in high-quality forums. We expect the applicants to have a PhD degree (or close to completing one) in computer science, mathematics or statistics, with
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
models. You will also have opportunities to contribute to open-source computational tools and datasets, teach master-level courses, and advise doctoral students. You will closely collaborate with Prof
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-in-cell computer codes hosted on local and national high-performance computing clusters; establishing all-optical diagnostics to map temperature evolution in plasma accelerators; exploring novel inter
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proof-of-principle repetition-rate and staging experimentation. The successful candidate will perform duties that include developing/using particle-in-cell computer codes hosted on local and national high
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approaches and the high precision of dynamic approaches. The successful candidate will: You will have a PhD in Computer Science (or be near completion) with a strong research record in one or more of the
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advanced material coating strategies. The project addresses the growing need to improve the surface properties and stability of LFP materials, especially under high-performance applications. Traditional
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Postdoctoral Research Associate on Quantum Networking ( Job Number: 26000032) Department of Computer Science Grade 7: - £38,784- £41,064 per annum Fixed Term - Full Time Contracted Hours per Week
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of the training process in Premier League football players. This is a unique opportunity for an enthusiastic, collegial, and high-performing researcher seeking to embed themselves in a high-performance sporting
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to develop a program of work investigating how brains use internal models of task and world structure to enable flexible goal-directed behaviour. The experiments will involve recording and/or manipulating
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Revolution with Ultra-Low Energy 2D Materials and Devices (NEED2D)." The project focuses on cutting-edge research into the growth, characterisation, and application of high-performance two-dimensional (2D